Integrating UAV Multispectral Indices (NDVI) with Yield Data for Optimizing Flax (Linum usitatissimum L.) Cultivation

Abstract

Flax (Linum usitatissimum L.), is a multipurpose crop, grown for fiber, seeds, and oil. This study aims to assess flax growth dynamics and agronomic traits using Normalized Difference Vegetation Index (NDVI) maps generated from multispectral imagery captured by an Unmanned Aerial Vehicle (UAV). Conducted at the Agricultural University of Athens, the field experiment followed a split-plot design with four replicates, encompassing various sowing distances (30 and 40 cm, between rows) and fertilization treatments (urea fertilization, urea with inhibitors, organic fertilizer). NDVI index maps were produced at key growth stages (60, 90, 120, 150, and 179 Days After Sowing) to facilitate comprehensive growth analysis. The findings indicate that while fertilization treatments and sowing densities influenced early growth stages, no significant differences were observed post 90 DAS. NDVI values correlated with agronomic traits, particularly during the early vegetative phase, highlighting the potential of UAV-based NDVI mapping for precise flax cultivation monitoring.